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Record W36873316 · doi:10.1016/j.hroo.2022.12.012

A High-Performance GriFTP Server at Desktop Cost

2007· article· en· W36873316 on OpenAlexaff
Samer Al-Kiswany, Armin Bahramshahry, Hesam Ghasemi, Matei Ripeanu, Sudharshan S. Vazhkudai

Bibliographic record

VenueHeart Rhythm O2 · 2007
Typearticle
Languageen
FieldComputer Science
TopicDistributed and Parallel Computing Systems
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer scienceBottleneckComputer networkFile serverOperating systemFile systemSoftware deploymentData accessComputer data storageBandwidth (computing)Replication (statistics)Distributed computingEmbedded systemDatabase

Abstract

fetched live from OpenAlex

Abstract-- We prototype a storage system that provides the access performance of a well-endowed GridFTP deployment (e.g., using a cluster and a parallel file-system) at the modest cost of single desktop. To this end, we integrate GridFTP and a combination of dedicated but low-bandwidth (thus cheap) storage nodes and scavenged storage from LAN-connected desktops that participate intermittently to the storage pool. The main advantage of this setup is that it alleviates the server I/O access bottleneck. Additionally, the specific data access pattern of GridFTP, that is, the fact that data accesses are mostly sequential, allows for optimizations that result in a high-performance storage system. To provide data durability when facing intermittent participation of the storage resources, we use an intelligent replication scheme that minimizes the volume of internal transfers that impact the low-bandwidth storage nodes. The Problem. GridFTP [1] extends the FTP protocol with new features such as striping and partial file access. GridFTP has become the data access and management protocol of choice for Grid deployments in data-intensive scientific communities. As a result, significant efforts have been made to optimize the protocol itself and the software stack implementing it, and, more relevant to our work, often, GridFTP deployments are supported by expensive hardware resources that enable high storage I/O access rates (e.g., clusters and parallel file systems). The protocol has been itself modified in order to be able to take

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.244
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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